The present invention relates to computer control which utilizes a knowledge information processing technique in order to determine an optimal control strategy, and more particularly to a computer control system which determines an optimal one of a set of mathematical models, which represents a control strategy, and applies the model in performing the real control by using the knowledge information processing technique.
In a computer control system or more broadly an information processing system, the control method or strategy of the system is represented by a mathematical model, and the model is translated to a programming code in order to apply the mathematical model to the real system. For instance, control objects of the process control system are described by the mathematical model, and they are used to realize an optimal control under various operations of the plant.
However, the given mathematical model is not always optimal under all operations.
Where the plant is complex or a characteristic of the plant is not clear and cannot be fully grasped, it is not uncommon that a control method is determined by an operational experience (know-how) of an operator. Usually, the more experience the operator has, the better will be the control method selected. Further, when an operation sequence is changed or an operation which has not been included in an initial plan is added to the system, the mathematical model and many parts of a developed program must be modified or another new program must be developed again. Various errors may be introduced during this process, and this may cause the following problems.
(i) System trouble due to bugs included in the corrected or added program.
(ii) Big effect to correct or add the program.
It is difficult to perfectly avoid errors when correction of the program is carried out manually. Typical example thereof is a combustion control of a reheating furnace in a rolling plant. The reheating furnace heats various types and sizes of materials. A real-time digital control system (IFAC, Jan. 17-20, 1983, IFAC/IFIP Symposium) has been developed for the control of the heating furnace. In such a control system, the program must be corrected or added to when the control object changes. Thus, bugs are introduced and a big effort is needed for debugging. When a new mathematical model (or formulas) is given, we must derive a relationship between the mathematical formulas, determine an algorthm for searching for a solution which satisfies the mathematical formulas and convert the relationship and the algorithm to a program. Accordingly, when a new mathematical formula is added or any formula in the system must be modified, many parts of the program must be amended.
Though the correction and development of the program are usually done by system engineers or programmers, it is difficult to perfectly prevent errors in each step of converting the mathematical formulas to the program.
We encounter a similar problem in the control system of a turbine or boiler of a thermoelectric power plant, and in a system which is based on a modern control theory, in which control strategies are represented by cost functions and restriction functions.